Almonds and Biomarkers of Lipid Peroxidation: A Randomized Controlled Cross‐over Trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Nut consumption is associated with a reduced risk of coronary heart disease (CHD). Almonds, in addition to their cholesterol‐lowering properties, have been shown to reduce oxidized LDL concentrations. However, their effect on other markers of lipid peroxidation is unknown. Methods: Twenty seven men and women with hyperlipidemia consumed 3 iso‐energetic (mean 423 kcal/d) supplements as part of their therapeutic diets for 1 month each. Supplements consisted of full‐dose almonds (73±3g/d), half‐dose almonds plus half‐dose muffins and full‐dose muffins. Subjects were assessed at wks 0, 2 and 4. Results: At 4 wks, the full‐dose almonds significantly reduced serum concentrations of malondialdehyde (MDA) (P=0.040) and creatinine‐adjusted urinary isoprostane output (P=0.026) compared to the full‐dose muffins. No effect was seen in serum levels of α‐ or γ‐ tocopherol, adjusted or unadjusted for total cholesterol. Conclusion: Almond consumption significantly decreased oxidative damage to 2 additional biomarkers of lipid peroxidation, serum MDA and urinary isoprostanes, further supporting our previous finding that almonds reduced the oxidation of LDL. This provides a further mechanism, in addition to cholesterol‐lowering, that may account for the reduction in CHD risk associated with nut consumption. Funding support: Almond Board of California
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it